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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2016 Vol.17 No.3 P.265-280
Adaptive robust beamformer for multi-pair two-way relay networks with imperfect channel state information
Abstract: In wideband multi-pair two-way relay networks, the performance of beamforming at a relay station (RS) is intimately related to the accuracy of the channel state information (CSI) available. The accuracy of CSI is determined by Doppler spread, delay between beamforming and channel estimation, and density of pilot symbols, including transmit power of pilot symbols. The coefficient of the Gaussian-Markov CSI error model is modeled as a function of CSI delay, Doppler spread, and signal-to-noise ratio, and can be estimated in real time. In accordance with the real-time estimated coefficients of the error model, an adaptive robust maximum signal-to-interference-and-noise ratio (Max-SINR) plus maximum signal-to-leakage-and-noise ratio (Max-SLNR) beamformer at an RS is proposed to track the variation of the CSI error. From simulation results and analysis, it is shown that: compared to existing non-adaptive beamformers, the proposed adaptive beamformer is more robust and performs much better in the sense of bit error rate (BER); with increase in the density of transmit pilot symbols, its BER and sum-rate performances tend to those of the beamformer of Max-SINR plus Max-SLNR with ideal CSI.
Key words: Multi-pair two-way relay, Adaptive robust beamformer, Channel state information (CSI), Maximum signal-to-interference-and-noise ratio (Max-SINR), Maximum signal-to-leakage-and-noise ratio (Max-SLNR)
创新点:建模Gaussian-Markov误差模型中的信道估计误差系数为反馈时延、多普勒扩展和信噪比的联合函数。在此基础上,构建一种基于最大化信干噪比和最大化信泄噪比准则的自适应稳健波束成形算法。
方法:首先,根据Gaussian-Markov信道估计误差模型,利用统计理论,设计一种不完全信道状态信息下基于最大化信干噪比和最大化信泄噪比准则的波束成形算法。然后,将信道估计误差模型系数建模为反馈时延、多普勒扩展和信噪比的联合函数。通过实时估计CSI时延和信道估计器引起的误差系数,实时设计匹配于信道变化的稳健波束成形器。最后,通过仿真结果验证该算法的正确性、稳健性和自适应性。
结论:仿真表明:提出的自适应稳健波束成形算法误码率性能明显优于现有的非自适应算法,并且随着导频符号数目的增加,该算法的性能会逐渐趋于理想CSI条件下的性能。
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DOI:
10.1631/FITEE.1500134
CLC number:
TN929.5
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On-line Access:
2024-08-27
Received:
2023-10-17
Revision Accepted:
2024-05-08
Crosschecked:
2016-01-28